In silico drug screening by using genome-wide association study data repurposed dabrafenib, an anti-melanoma drug, for Parkinson's disease

Takeshi Uenaka, Wataru Satake, Pei Chieng Cha, Hideki Hayakawa, Kousuke Baba, Shiying Jiang, Kazuhiro Kobayashi, Motoi Kanagawa, Yukinori Okada, Hideki Mochizuki, Tatsushi Toda

Research output: Contribution to journalArticlepeer-review

37 Scopus citations

Abstract

Parkinson's disease (PD) is a neurodegenerative disorder characterized by dopaminergic neuron loss. At present, there are no drugs that stop the progression of PD. As with other multifactorial genetic disorders, genome-wide association studies (GWASs) found multiple risk loci for PD, although their clinical significance remains uncertain. Here, we report the identification of candidate drugs for PD by a method using GWAS data and in silico databases. We identified 57 Food and Drug Administration-approved drug families as candidate neuroprotective drugs for PD. Among them, dabrafenib, which is known as a B-Raf kinase inhibitor and is approved for the treatment of malignant melanoma, showed remarkable cytoprotective effects in neurotoxin-treated SH-SY5Y cells and mice. Dabrafenib was found to inhibit apoptosis, and to enhance the phosphorylation of extracellular signal-regulated kinase (ERK), and inhibit the phosphorylation of c-Jun NH2-terminal kinase. Dabrafenib targets B-Raf, and we confirmed a protein-protein interaction between B-Raf and Rit2, which is coded by RIT2, a PD risk gene in Asians and Caucasians. In RIT2-knockout cells, the phosphorylation of ERK was reduced, and dabrafenib treatment improved the ERK phosphorylation. These data indicated that dabrafenib exerts protective effects against neurotoxicity associated with PD. By using animal model, we confirmed the effectiveness of this in silico screening method. Furthermore, our results suggest that this in silico drug screening system is useful in not only neurodegenerative diseases but also other common diseases such as diabetes mellitus and hypertension.

Original languageEnglish
Pages (from-to)3974-3985
Number of pages12
JournalHuman Molecular Genetics
Volume27
Issue number22
DOIs
StatePublished - 1 Nov 2018
Externally publishedYes

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